Towards Coexistence of Human and Robot: How Ubiquitous Computing Can Contribute?

After the ISO 10218-1/2 in 2011, safety factors for industry robot are standardized. As robotics expands its area from industry further into service, educational, healthcare and etc., both human and robot are exposed to a space with more openness and less certainty. Because there is no common safety specification, we raise in this paper our own hypotheses on the safety requirements in dense human-robot co-existing scenarios and focus more on demonstrating the possibilities provided by the research field named Ubiquitous Computing.

[1]  S. Iyengar,et al.  Multi-Sensor Fusion: Fundamentals and Applications With Software , 1997 .

[2]  Kai Kunze,et al.  Who are you?: A wearable face recognition system to support human memory , 2013, AH.

[3]  Bernard C. Jiang,et al.  A cause-and-effect analysis of robot accidents , 1987 .

[4]  Franco Zambonelli,et al.  Pervasive pheromone-based interaction with RFID tags , 2007, TAAS.

[5]  T. Sanpechuda,et al.  A review of RFID localization: Applications and techniques , 2008, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[6]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[7]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

[8]  François Marx,et al.  Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning , 2006, EURASIP J. Adv. Signal Process..

[9]  Kaveh Pahlavan,et al.  Modeling of the TOA-based distance measurement error using UWB indoor radio measurements , 2006, IEEE Communications Letters.

[10]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[11]  Karsten Berns,et al.  3D Audio Perception System for Humanoid Robots , 2009, 2009 Second International Conferences on Advances in Computer-Human Interactions.

[12]  Helena Leppäkoski,et al.  Pedestrian Navigation Based on Inertial Sensors, Indoor Map, and WLAN Signals , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[13]  Paul Lukowicz,et al.  A Wearable, Conductive Textile Based User Interface for Hospital Ward Rounds Document Access , 2008, EuroSSC.

[14]  Fabio Paternò,et al.  Scan and tilt: towards natural interaction for mobile museum guides , 2006, Mobile HCI.

[15]  Avinash C. Kak,et al.  Vision for Mobile Robot Navigation: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Venkata N. Padmanabhan,et al.  Indoor localization without the pain , 2010, MobiCom.

[17]  Aude Billard,et al.  Safety issues in human-robot interactions , 2013, 2013 IEEE International Conference on Robotics and Automation.

[18]  Ronald C. Arkin.  Homeostatic control for a mobile robot: Dynamic replanning in hazardous environments , 1992, J. Field Robotics.

[19]  Alin Albu-Schäffer,et al.  Safety Evaluation of Physical Human-Robot Interaction via Crash-Testing , 2007, Robotics: Science and Systems.

[20]  Paul Lukowicz,et al.  From Smart Clothing to Smart Table Cloth: Design and Implementation of a Large Scale, Textile Pressure Matrix Sensor , 2014, ARCS.

[21]  Martin Hägele,et al.  Dependable Interaction with an Intelligent Home Care Robot , 2001 .

[22]  Paul Lukowicz,et al.  Robust, low cost indoor positioning using magnetic resonant coupling , 2012, UbiComp.

[23]  Giulio Sandini,et al.  An embedded artificial skin for humanoid robots , 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

[24]  Wolfram Burgard,et al.  A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).